Present invention embodiments relate to navigation systems, and more specifically, to route generation for navigation systems based on contextual risk.
As the Internet of Things (IoT) expands to include all sorts of devices, such as kitchen appliances, fitness trackers, alarm clocks, thermostats, vehicles, etc., an immense amount of data is being generated. For vehicles in particular, multiple device types facilitate the generation of large amounts of telematics data that allow vehicles to be tracked over different routes. Currently, this data is being used to help track and resolve traffic issues. Moreover, car insurance providers are beginning to use telematics data to implement pay-as-you-go programs or otherwise adjust premiums to specific rates for specific drivers. However, sometimes this telematics data fails to provide the adequate information because it is provided without context. For instance, if telematics data indicates that a driver is frequently braking hard, the data does not clarify whether the driver is avoiding accidents that others might have caused (and, thus, for insurance purposes might deserve lower rates) or driving recklessly (and, thus, for insurance purposes might deserve higher rates).
Moreover, regardless of insurance rates, driving safety (e.g., minimizing risk) is a critical factor for many drivers or family members (e.g., parents concerned about their teenage drivers), especially for special groups of drivers like senior citizens, teenagers, new drivers, people with disabilities, etc. As advances in technology pervade automobiles and automobile-related equipment (e.g., rearview cameras, blind spot cameras/alerts, etc.), risks of driving are being reduced. However, driving still has at least some amount risk associated with it.
For example, driving safety is not only related to personal driving habits and behavior patterns, but also to driving environmental context (e.g., weather, traffic, road type, road condition, terrain, day/night time, accident data, crime data), which may be largely dependent of the specific route that a driver will select. In addition, the personal characteristics of individual drivers are not taken into consideration in telematics data. For example, the likelihood of dangerous driving behavior (under a specific context) varies by individual drivers and the risk level for driving on the same route versus a new route should be different. Although many navigation applications now take traffic and customer preference (e.g., minimize or maximize highway driving) into account, none determine risk in order to allow a driver to select the safest, least risky path. Moreover, although some systems generate a route with consideration of statistics risk index on each road segment, these systems do not consider dynamic environmental attributes like traffic, weather, road condition (slippery, icy), accident and crime history in order to determine a contextual risk for a road. Moreover, current systems do not correlate contextual risk with personal driving characteristics (e.g., driver-associated risk) to derive the least risky route for the specific driver at an exact, real-time moment.